Questions tagged [keras]

For questions related to Keras, the modular neural networks library written in Python. However, note that programming questions are off-topic here.

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16 views

Generation of realistic real-valued sequences using Wasserstein GAN fails

My goal is to generate artificial sequences of real-valued data (e.g. time series) with GANs. Starting simple I tried to generate realistic sine-waves using a Wasserstein GAN. But even on this simple ...
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2answers
59 views

Training accuracy vs validation accuracy on deep models

I'm training a deep network in Keras on some images for a binary classification (I have around 12K images). Once in a while, I collect some false positives and add ...
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29 views

How would I go about performing a single step of gradient descent on this model?

I have a classification model that consists of a CNN followed by an SVM. I used the Keras library for the CNN portion and sklearn for the SVM portion. I am assuming I will have to fiddle with the ...
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6answers
9k views

Why do CNN's sometimes make highly confident mistakes, and how can one combat this problem?

I trained a simple CNN on the MNIST database of handwritten digits to 99% accuracy. I'm feeding in a bunch of handwritten digits, and non-digits from a document. I want the CNN to report errors, so I ...
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1answer
3k views

Tensorflow-gpu cannot use Nvidia GPU with CUDA [closed]

I'm working on a Python Keras/Tensorflow image recognition script (on Ubuntu 18.04) which works ok, but it will only train on CPU (which is slow) and I want to be using my GPU (i have a Nvidia Geforce ...
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0answers
15 views

How do I build a multi RNN network with keras?

I have 2 (independently long) sequences (a and b) of feature vectors that I want to use as input for a neural network. The idea was to build 2 GRU based encoders (one for each sequence). I would than ...
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0answers
28 views

How to use Before / After images to train a model

I am trying to create a model that can clean pictures of noise, blur, high luminosity etc, but I do not know how to do that. I have tried to search for it a lot, and I couldn't find anything that ...
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0answers
32 views

How can I train a Deep Learning model using degraded photos and their clean version to correct photos

I have 5000 degraded pictures ( pixelated, blurry, too much luminosity ... ) and their clean versions, and I would like to train a model so that it can predict how to correct future pictures. I've ...
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3answers
193 views

Why are traditional ML models still used over deep neural networks?

I'm still on my first steps in the Data Science field. I played with some DL frameworks, like TensorFlow (pure) and Keras (on top) before, and know a little bit of some "classic machine learning" ...
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0answers
31 views

Reversing A Keras Dense GAN

I have a Keras GAN where every layer in the generator has more neurons than the last and also where they all have an activation of LeakyReLU(alpha=0.1). I am trying to map the image back to the noise ...
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2answers
1k views

Effect of batch size and number of GPUs on model accuracy

I have a data set which was split using a fixed random seed and I am going to use 80% of data for training and rest on validation. Here are my GPU and batch size configurations use ...
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4answers
2k views

How to reproduce neural network training with keras [closed]

I want to see the effects of changing some training parameters (batch size, learning rate, optimizer...) to the accuracy obtained. The problem is that with the same parameters I get significantlly ...
3
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1answer
102 views

Can dropout layers not influence LSTM training?

I am working on a project that requires time-series prediction (regression) and I use LSTM network with first 1D conv layer in Keras/TF-gpu as follows: ...
2
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0answers
96 views

Is it possible to use entity embedding with autoencoder for anomaly detetction?

I'm trying to build autoencoder in keras in order to detect anomalies. However, most of the data is categorical and I have to encode it. When it comes to production, categorical features can take new ...
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0answers
436 views

Reasoning behind $Zero$ validation accuracy in the following ResNet50 model for classification

I have written this code to classify Cats and dogs using Resnet50. Actually while studying I came to the conclusion that Transfer learning gives very good accuracy for deep learning models, but I ...
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1answer
54 views

not sure if fine-tuned network is finely-tuned

I am practicing with Resnet50 fine tuning for binary classification task, here is my code snippet. ...
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0answers
38 views

Can anyone explain the pixelwise accuracy metric used in this paper? Also a question to the KL Divergence Loss

So I am making a project based on this paper: https://arxiv.org/ftp/arxiv/papers/1901/1901.07761.pdf In this paper, a U-Net is used to generate optimized mechanical structures. I am trying to ...
3
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1answer
46 views

How to describe an keras Model in a scientific report

how would you describe a machine learning model in a scientific report? It should be detailed but I just listed the hyperparameters... Have you got more important properties?
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1answer
341 views

How many parameters are being optimised over in a simple CNN?

Okay so here's my CNN (simple example from a tutorial) along with some arithmetic to get the total number of free parameters. We've got a dataset of 28*28 grayscale image (MNIST). First layer is a ...
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0answers
29 views

How to handle a high dimensional video (large number of frames per video) data for training a video classification network

I have a video dataset as follows. Dataset size: 1k videos Frames per video: 4k (average) and 8k (maximum) Labels: Each video has one label. So the size of my input will be (N, 8000, 64, 64, 3) ...
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0answers
25 views

Can't figure out what's going wrong with my dataset construction for multivariate regression

TL;DR: I can't figure out why my neural network wont give me a sensible output. I assume it's something to do with how I'm presenting the input data to it but I have no idea how to fix it. Background:...
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0answers
26 views

How are batch statistics computed in Recurrent Batch Normalization?

I'm implementing recurrent BN per this paper in Keras, but looking at it and those citing it, a detail remains unclear to me: how are batch statistics computed? Authors omit explicit clarification, ...
2
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1answer
1k views

How to compute number of weights of CNN?

How can we compute number of weights considering a convolutional neural network that is used to classify images into two classes : INPUT: 100x100 gray-scale images. LAYER 1: Convolutional layer with ...
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1answer
166 views

Deep Learning models train really slow Jetson Nano [closed]

I recently bought a Jetson Nano and I'm amazed with everything about it. But I don't know what is happening, because I created a very simple neural network with keras and it's taking way to long. I ...
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0answers
42 views

What is the correct input shape for my LSTM network?

My professor gave us a workshop where we have to do classification of a dataset of ECG signals between healthy and unhealthy types using LSTM. Each signal consists of 1,285 time steps. What my prof ...
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1answer
34 views

Is CNN capable of extracting the descriptive statistics features

I was trying to build a CNN model. I used time series data of daily temperature to predict if there is risk of an event, say bacteria growth. I calculated the descriptive statistics of the time series,...
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0answers
29 views

Does a varying ANN model accuracy mean underfitting or overfitting?

Background: This is for a simulated robot with four legs, walking on a flat terrain. The ANN (an MLP) is given inputs as the robot's body angle, positions and angle of each leg with respect to the ...
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0answers
26 views

Applying Machine Learning to 2D Laser Scanner Data

We are using 2D Laser Scanner to scan various objects of different geometric shapes for e.g. cylinder, spiked, cylinder with notch, cylinder with curved edges e.t.c. The dataset contains points in the ...
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0answers
39 views

How to perform regression with multiple numeric (positive and negative) inputs and one numeric output?

I have a dataset with different types of numerical values (both negative and positive numerical values) for the inputs (for example, -40, -35, 1, 25, 39, etc., that is, multiple inputs) and single ...
2
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1answer
69 views

How to reduce variance of the model loss during training?

I know that stochastic gradient descent always gives different results. What are the best practices to reduce this variance today? I tried to predict simple function with two different approaches and ...
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0answers
21 views

Keras correlation coefficient as network metric in R

does anyone know how to use the correlation coefficient or squared correlation coefficient as a metric in keras in R (although other languages may provide clues). This is for a CNN that functions ...
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0answers
30 views

How to change the architecture of my simple sequential model

I'm new to Deep Learning with Keras. With some tutorials online for cat vs non-cat classification, I was able to compile this simple architecture for my own ...
2
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1answer
51 views

Multi label Classification using Keras

I am trying to build a Multi label classification model, having dataset with different input numerical values and specific label... Eg: Value Label 35 X 35.8 X 29 Y 29.8 Y 39 AA 41 CB ...
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1answer
47 views

Techniques and semantics in better training of deep learning models [closed]

I'm relatively new to Deep Learning, and trying various models and datasets using Keras. I'm starting to love it! Through-out my experimentations, I have come into ...
2
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1answer
33 views

Semantic issues with predictions made by my trained model

I'm new to Deep Learning. I used Keras and trained a inception_resnet_v2 model for my binary classification application (fire ...
3
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1answer
1k views

ValueError: Error when checking target: expected dense_3 to have shape (1,) but got array with shape (2,)

I am trying to build a CNN model on Keras. The data has a dimension of 921 rows × 10000 columns. Here is the code: ...
2
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1answer
45 views

How to represent integer values in sequence to sequence prediction task in encoder-decoder LSTM?

I have a large 2D grid having 30k rows and 35k columns, so a total of 30x35k grid cells. Each grid cell is represented by a unique integer number (identity of grid cell). I have several trajectories ...
4
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1answer
107 views

What is the fastest way to train a CNN with billions of examples?

I have a CNN model that I need to train for a large scale genomics application. It is working well with a subset of my training data. I have scaled up to a subset of about 130 million examples and ...
5
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1answer
422 views

How do I combine models trained on different data to increase classification accuracy?

I have two trained models. One is using a LinearSVC algorithm and is trained on numerical data from medical examination from patients with diabetic retinopathy. The second one is a neural network ...
2
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0answers
44 views

Which deep neural networks are appropriate for the detection of bombs?

This is a follow-up question from my previous post here about explosion detection. I gathered a dataset of explosions. As I'm new to Deep Learning in Keras, I'm trying to see what architecture best ...
3
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0answers
108 views

How can I increase the speed and performance of my implementation of an AI for Reversi?

I made an AI for Reversi, aka Othello (8×8), like Alpha Zero, using this book. This book is written in Japanese. The source code of the AI I implemented can be found in this Github repository. There ...
4
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2answers
41 views

Using a neural network to identify a stable region within a set of data?

I am working on a problem in which I am attempting to find a stable region in a spiral galaxy. The PI I'm working with asked me to use machine learning as a tool to solve the problem. I have created ...
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0answers
30 views

How to implement CNN with variable number of images in tensorflow or keras?

Suppose I have a problem where I want to classify the color of LEDs seen in the image. I can use OpenCV to pinpoint the exact location of these LEDs but I do not know their color for sure because the ...
2
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1answer
111 views

Why is this ResNet50 misclassifying objects?

I'm new to Deep Learning, and I have some conceptual problems. I followed a simple tutorial here, and trained a model in Keras to do image classification on 10 classes of logos. I prepared 10 classes ...
2
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1answer
27 views

The best way of classifying a dataset including classes with high similarity?

I have a dataset which has two very similar classes (men wrestling, women wrestling). I've used InceptionV3 as a classifier to solve the problem of classifying this dataset. Unfortunately, the ...
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1answer
63 views

How can we print weights per iteration in a simple feed forward MLP for an specific class?

im working on a project in which I have to make a multi-layer perceptron with two hidden layers with 3 nodes in each. The target value in my data contains 8 unique values/classes. One of the tasks ...
1
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1answer
107 views

Which model can I use for this problem with multiple inputs and outputs?

Which model is the most appropriate for this problem with multiple inputs and outputs? The data set is A1, A2, A3, A4, A5, A6, B1, B2, B3, B4 where ...
4
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1answer
110 views

What is the best approach for multivariable and multivariate regression?

I want to build a multivariable and multivariate regression model in Keras (with TensorFlow as backend), that is, a regression model with multiple values as input (multivariable) and output (...
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1answer
65 views

TF Keras: How to turn this probability-based classifier into single-output-neuron label-based classifier

Here's a simple image classifier implemented in TensorFlow Keras (right click to open in new tab): https://colab.research.google.com/github/tensorflow/docs/blob/master/site/en/tutorials/quickstart/...
3
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1answer
512 views

How can I reduce the GPU memory usage with large images?

I am trying to train a CNN-LSTM model. The size of my images is 640x640. I have a GTX 1080 ti 11GB. I am using Keras with the TensorFlow backend. Here is the model. ...